cnComplexity: Network Complexity

In catnet: Categorical Bayesian Network Inference

Network Complexity

Description

Returns the complexity of a network

Usage

cnComplexity(object, node=NULL, include.unif=TRUE)
cnKLComplexity(object, node=NULL)

Arguments

object	a catNetwork object
node	an integer, node index
include.unif	a logical

Details

Complexity is a network characteristics that depends both on its graphical structure and the categorization of its nodes.

If node is specified, then the function returns that node complexity, otherwise the total complexity of object, which is the sum of its node complexities, is reported. A node complexity is determined by the number of its parents and their categories. For example, a node without parents has complexity 1. A node with k parents with respected number of categories c1,c2, ...,ck, has complexity c1*c2*...*ck. Complexity is always a number that is equal or greater than the number of nodes in the network. For a network with specified graph structure, its complexity determines the number of parameters needed to define its probability distribution and hence the importance of complexity as network characteristic.

If include.unif is set to FALSE

Value

An integer

Author(s)

N. Balov, P. Salzman

Examples

  library(catnet)
  cnet <- cnRandomCatnet(numnodes=10, maxParents=3, numCategories=2)
  cnComplexity(object=cnet)

catnet documentation built on Nov. 10, 2022, 5:08 p.m.